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Using qualitative approach to forecasting regime switches

Author

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  • Kun-Huang Huarng

    (Feng Chia University)

  • Tiffany Hui-Kuang Yu

    (Feng Chia University)

Abstract

Drastic changes (named regime switches) often exist in economic and financial time series causing the forecasting of time series difficult. Hence, we need robust models to detect and forecast the regime switches. Most previous studies apply quantitative methods to forecast time series and regime switches. Contrast to these studies, this study attempts a novel approach to use a qualitative method to forecast regime switches. Fuzzy set/qualitative comparative analysis (fsQCA), based on fuzzy set and logic theory, yields the relationships between antecedent combinations and outcome. Studies support fsQCA analysis is more proper to reflect the real situations. Hence, this study uses fsQCA to analyze the autoregressive relationships of the upward and downward regime switches in the in-sample data. Then, the relationships are used to forecast the regime switches in the out-of-sample data. Taiwan Capitalization Weighted Stock Index is taken as the data for analysis. The empirical results show that fsQCA provides strong predictive validities.

Suggested Citation

  • Kun-Huang Huarng & Tiffany Hui-Kuang Yu, 2017. "Using qualitative approach to forecasting regime switches," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2035-2048, September.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:5:d:10.1007_s11135-016-0338-x
    DOI: 10.1007/s11135-016-0338-x
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    References listed on IDEAS

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    1. Thomas Denk & Sarah Lehtinen, 2014. "Contextual analyses with QCA-methods," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3475-3487, November.
    2. Huarng, Kun-Huang, 2015. "Configural theory for ICT development," Journal of Business Research, Elsevier, vol. 68(4), pages 748-756.
    3. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    4. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2015. "Healthcare expenditure with causal recipes," Journal of Business Research, Elsevier, vol. 68(7), pages 1570-1573.
    5. Bettina Trueb, 2013. "Integrating qualitative and quantitative data: index creation using fuzzy-set QCA," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(6), pages 3537-3558, October.
    6. Barbara Vis & Jaap Woldendorp & Hans Keman, 2013. "Examining variation in economic performance using fuzzy-sets," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 1971-1989, June.
    7. Tang, Yinan & Chen, Ping, 2014. "Time varying moments, regime switch, and crisis warning: The birth–death process with changing transition probability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 56-64.
    8. Shiro Kuwahara, 2013. "Dynamical analysis of the R&D-based growth model with a regime switch," Journal of Economics, Springer, vol. 108(1), pages 35-57, January.
    9. Huarng, Kun-Huang, 2016. "Identifying regime switches using causal recipes," Journal of Business Research, Elsevier, vol. 69(4), pages 1498-1502.
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    Cited by:

    1. Kumar, Satish & Sahoo, Saumyaranjan & Lim, Weng Marc & Kraus, Sascha & Bamel, Umesh, 2022. "Fuzzy-set qualitative comparative analysis (fsQCA) in business and management research: A contemporary overview," Technological Forecasting and Social Change, Elsevier, vol. 178(C).

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